Sensitivity enhancement of thermal lens spectrometry
Bibliographic record
Abstract
Thermal lens spectrometry has been utilized in various applications, and in some application areas, high sensitivity is required. In this work, a mode-mismatched thermal lens configuration probing thermal lens twice was developed for sensitivity enhancement. Experimental results exhibited that doubled sensitivity was achieved with this configuration compared with that attained with a conventional one, which was consistent with the prediction of the theoretical model for thermal lens spectrometry. As a result of the consistency, the linear absorption (attenuation) coefficient of de-ionized water at 532.3 nm was directly measured with this configuration and the conventional one and found to be (4.90 ± 0.05) × 10−2 m−1 and (4.7 ± 0.2) × 10−2 m−1, respectively. The results are in good agreement with accepted literature values. Theoretical analysis revealed that the sensitivity enhancement with this configuration is greater than that by simply doubling the sample thickness in a conventional configuration.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".